Level Of Resolution Research Articles

Integration of single-cell datasets depicts profiles of macrophages and fibro/adipogenic progenitors in dystrophic muscle

Single-cell technologies have recently expanded the possibilities for researchers to gain, at an unprecedented resolution level, knowledge about tissue composition, cell complexity, and heterogeneity. Moreover, the integration of data coming from different technologies and sources also offers, for the first time, the possibility to draw a holistic portrait of how cells behave to sustain tissue physiology during the human lifespan and disease.Here, we interrogated and integrated publicly available single-cell RNAseq data to advance the understanding of how macrophages, fibro/adipogenic progenitors, and other cell types establish gene regulatory networks and communicate with each other in the muscle tissue. We identified altered gene signatures and signaling pathways associated with the dystrophic condition, including an enhanced Spp1-Cd44 signaling in dystrophic macrophages. We shed light on the differences among dystrophic muscle aging, considering wild type, mdx, and more severe conditions as in the case of the mdx-2d model. Contextually, we provided details on existing communication relations between muscle niche cell populations, highlighting increased interactions and distinct signaling events that these cells stablish in the dystrophic microenvironment.We believe our findings can help scientists to formulate and test new hypotheses by moving towards a more complete understanding of muscle regeneration and immune system biology.

Vegetation Change Detection Analysis Using Multi-sensor Hyperspectral Imagery

Vegetation is a fundamental component of ecosystems that maintains carbon levels, hydrological cycles, mitigating greenhouse gases, and ensures climate stability. In recent years, the impacts of global climate change have led to changes in vegetation cover at various levels. Efforts to monitor changes in vegetation are important and beneficial for various fields such as forest monitoring, agriculture, and plantations, among others. The main objective of this research is to detect changes both increase and decrease in vegetation using multi-sensor hyperspectral imagery. The hyperspectral images used in this study are Hyperion 2014 and PRISMA 2021. The method involves creating different levels of spectral resolution simulations from hyperspectral images to detect vegetation changes. Meanwhile, the vegetation change Clustering method employs unsupervised (k-means) techniques. The cluster results can indicate vegetation changes such as vegetation degradation, vegetation, devegetation, or no change, though they currently have low accuracy. The highest accuracy is by Simulated RapidEye image simulations, is 33.5%. The low accuracy results attributed insufficient preprocessing, particularly in topographic correction. Additionally, this research indicates that the spectral resolution levels do not have a significant impact on vegetation change detection, as the differences in change classes at each level are very small.

Exploring geography and evolutionary history as drivers of variation in floral scent chemistry in western sessile-flowered Trillium using parsimony-constrained phylogenetics.

The sessile-flowered Trillium species from western North America have been challenging to distinguish morphologically due to overlapping characters and intraspecific variation. Molecular phylogenetic analyses, currently inconclusive for this group, have not sampled multiple populations of the different species to account for this. Here, we query the diversity of floral volatile composition to understand its bearings on the taxonomy, distribution and evolution of this group. We explored taxonomic and geographic patterns in average floral volatile composition (105 different compounds) among 42 wild populations of four sessile-flowered Trillium species and the outgroup, Pseudotrillium, in California, Oregon and Washington by means of parsimony-constrained phylogenetic analyses. To assess the influence of character construction, we coded compound abundance in three different ways for the phylogenetic analyses and compared the results with those of statistical analyses using the same dataset and previously published statistical analyses. Different codings of floral volatile composition generated different phylogenetic topologies with different levels of resolution. The different phylogenies provide similar answers to taxonomic questions but support different evolutionary histories. Monophyly of most populations of each taxon suggests that floral scent composition bears phylogenetic signal in the western sessile-flowered Trillium. Lack of correlation between the distribution of populations and their position in scent-based phylogenies does not support a geographic signal in floral scent composition. Floral scent composition is a valuable data source for generating phylogenetic hypotheses. The way scent composition is coded into characters is important. The phylogenetic patterns supported by floral volatile compounds are incongruent with previously reported phylogenies of the western sessile-flowered Trillium obtained using molecular or morphological data. Combining floral scent data with gene sequence data and detailed morphological data from multiple populations of each species in future studies is needed for understanding the evolutionary history of western sessile-flowered Trillium.

Multi-omics integration for both single-cell and spatially resolved data based on dual-path graph attention auto-encoder.

Single-cell multi-omics integration enables joint analysis at the single-cell level of resolution to provide more accurate understanding of complex biological systems, while spatial multi-omics integration is benefit to the exploration of cell spatial heterogeneity to facilitate more comprehensive downstream analyses. Existing methods are mainly designed for single-cell multi-omics data with little consideration of spatial information and still have room for performance improvement. A reliable multi-omics integration method designed for both single-cell and spatially resolved data is necessary and significant. We propose a multi-omics integration method based on dual-path graph attention auto-encoder (SSGATE). It can construct the neighborhood graphs based on single-cell expression profiles or spatial coordinates, enabling it to process single-cell data and utilize spatial information from spatially resolved data. It can also perform self-supervised learning for integration through the graph attention auto-encoders from two paths. SSGATE is applied to integration of transcriptomics and proteomics, including single-cell and spatially resolved data of various tissues from different sequencing technologies. SSGATE shows better performance and stronger robustness than competitive methods and facilitates downstream analysis.

Monitoring Epoxidized Soybean Oil Degradation Using Liquid Chromatography-Mass Spectrometry and In Silico Spectral Libraries.

Epoxidized soybean oil (ESO) is routinely used as a bioderived plasticizer and stabilizer in polyvinyl chloride (PVC), as it prolongs material integrity during dehydrochlorination. During this process, the epoxide moieties of ESO are progressively converted to chlorohydrins, which amplify ESO's inherent structural complexity. Past characterization efforts utilized separation-mass spectrometry (MS) analysis of the hydrolyzed acyl chains to simplify the complexity. However, this approach significantly increases the complexity of sample preparation and cannot directly monitor the chlorination of individual ESO species during aging. Here, we present a comprehensive LC-MS/MS data acquisition and in silico spectral library identification workflow optimized for intact ESO byproduct analysis. Detailed MS/MS fragmentation rules derived from synthesized standards were coupled with improved fragment ion intensity modeling capabilities to generate a high-fidelity spectral library for rapid ESO byproduct identification. Identification confidence was further bolstered by using retention time modeling to filter spurious MS/MS matches. Finally, we paired this informatic approach with an optimized extraction procedure and reversed-phase separation to generate a detailed timeline of more than 400 ESO species and byproducts during PVC thermal aging. These developments significantly improve our ability to detect, characterize, and understand ESO degradation in complex PVC formulations with new levels of molecular resolution.

The myth of high-resolution liquid phase biological electron microscopy.

Cryo-electron microscopy (cryo-EM) has transformed structural biology over the past 12 years, with it now being routine rather than exceptional to reach a near-atomic level of resolution for proteins and macromolecular complexes. Samples are immobilized by vitrification and this sample can be maintained at liquid nitrogen temperatures in the vacuum of the electron microscope with negligible sublimation. Due to the low electron doses needed to avoid radiation damage, averaging over tens of thousands to hundreds of thousands of particle images is used to achieve a high signal-to-noise ratio. An alternative approach has been proposed where samples are at room temperature in the liquid state, maintained in the vacuum of the electron microscope by thin film enclosures that are relatively transparent to electrons while preventing evaporation of the liquid. A paper has argued that using this liquid-phase approach, higher resolution (3.2 Å) can be achieved than using cryo-EM (3.4 Å) when imaging and reconstructing adeno-associated virus particles. I show here that these assertions are untrue, and that basic principles in mathematics and physics would need to be violated to achieve the stated resolution in the liquid state. Thus, high resolution liquid phase EM of macromolecules remains science fiction.

Technostress in Nuclear Medicine: A Qualitative Study of Causes, Mitigators, and Resolution Levels

BackgroundIn contemporary healthcare, information and communication technology enables specialized treatment and efficient information sharing. However, it also causes stress and frustration, so-called technostress, among healthcare staff. PurposeTo investigate the day-to-day occurrence of technostress, we ask the research question: What causes the stressful situations with technology, how are they mitigated, and to what extent are they resolved? MethodWe interviewed 15 healthcare providers in the department of nuclear medicine at a Danish hospital about their experiences with technology-induced stress in their daily work. ResultsThe interviewees described 185 stressful situations with technology, mostly technology indispensable to their work. The two most frequent causes of stressful situations are system performance (46%) and technology-related organizational procedures (18%). To mitigate the situations, the most frequent strategies are accommodating (51%), consulting others for help (18%), and repeating previous task steps (13%). The mitigation strategies indicate that the stressful situations involve adapting work practices to the technology to a much larger extent than succeeding in adapting the technology to the work. Regarding the level of resolution, as much as 66% of the stressful situations are merely solved for now, that is, the concrete situation is resolved but the underlying issue remains unsolved. The underlying issue is resolved in only 10% of the situations, thereby indicating that the vast majority of the stressful situations are likely to recur later. ConclusionThe staff at the studied hospital department repeatedly experience stressful situations with the technology they rely on in their work. This technostress is an extra stressor on top of those induced by the staff’s responsibility for providing quality patient treatment. At the individual level, technostress leads to frustration and possibly burnout; at the organizational level, it calls for preventive action.

Friendship Network and School Socialization Correlates of Adolescent Ethnic-Racial Identity Development.

Ethnic-racial identity (ERI) development is consequential for youth adjustment and includes exploration, resolution, and affect about the meaning of one's ethnic-racial group membership. Little is known about how identity-relevant experiences, such as ethnic-racial socialization and discrimination in peer relationships and school contexts, catalyze adolescent ERI development. The present study examines how identity-relevant experiences in friend and school contexts (i.e., proportion of same-ethnoracial friends, cultural socialization among friends, friends' ERI dimensions, friends' experiences of ethnoracial discrimination, and school promotion of cultural competence and critical consciousness) are associated with ERI development. A multivariate path model with a sample from four southwestern U.S. schools (N = 717; 50.5% girls; Mage = 13.76; 32% Latinx, 31.5% Multiethnic, 25.7% White, 11% other) was used to test these associations. Findings showed that friend and school predictors of ERI did not differ between early and middle adolescents, but significant differences and similarities emerged in some of these associations between ethnoracially minoritized and White youth. Specifically, friend cultural socialization was positively associated with ERI exploration for ethnoracially minoritized youth only, whereas school critical consciousness socialization was positively linked with ERI exploration only for White youth. Friend cultural socialization and friend network's levels of ERI resolution were positively associated with ERI resolution across both ethnoracial groups. These friend and school socialization associations were documented above and beyond significant contributions of personal ethnoracial discrimination to ERI exploration and negative affect for both ethnoracially minoritized and White youth. These findings expand our understanding of how friend and school socialization mechanisms are associated with adolescent ERI development, which is vital to advancing developmental theory and fostering developmental competences for youth to navigate their multicultural yet socially stratified and inequitable world.

Histocompatibility assessment in hematopoietic stem cell transplantation: recommendations from the Italian Society for Immunogenetics and Transplantation Biology (Associazione Italiana di Immunogenetica e Biologia dei Trapianti - AIBT).

The outcome of allogeneic hematopoietic stem cell transplantation (HSCT) is significantly influenced by the degree of HLA histocompatibility between donor and recipient. To provide shared indications for required histocompatibility testing and interpretation before HSCT, the Italian Society for Immunogenetics and Transplantation Biology (Associazione Italiana di Immunogenetica e Biologia dei Trapianti [AIBT]) gathered members and created a working group to discuss and develop recommendations for histocompatibility assessment in HSCT.After a review of the literature and multiple panel discussions, AIBT developed up-to-date recommendations for the resolution levels of HLA typing, histocompatibility definitions of patients and donors, importance of anti-HLA antibodies, and significance of NK alloreactivity, which are reported in this document. These recommendations have been shared with the Italian Group for Bone Marrow Transplantation (Gruppo Italiano per il Trapianto di Midollo Osseo, cellule staminali emopoietiche e terapia cellulare [GITMO]) and the Italian National Center for Transplantation (Centro Nazionale Trapianti [CNT]). Notably, the increased use of HLA-mismatched transplantation (i.e., mismatched unrelated, haploidentical) in recent years has made these indications even more relevant for the standardization and improvement of quality of care.This document represents a useful instrument for health care workers involved in the field of HSCT, enhancing synergy with transplant physicians and enabling greater optimization of the available resources.

Advances in mass spectrometry imaging for plant metabolomics-Expanding the analytical toolbox.

Mass spectrometry imaging (MSI) has become increasingly popular in plant science due to its ability to characterize complex chemical, spatial, and temporal aspects of plant metabolism. Over the past decade, as the emerging and unique features of various MSI techniques have continued to support new discoveries in studies of plant metabolism closely associated with various aspects of plant function and physiology, spatial metabolomics based on MSI techniques has positioned it at the forefront of plant metabolic studies, providing the opportunity for far higher resolution than was previously available. Despite these efforts, profound challenges at the levels of spatial resolution, sensitivity, quantitative ability, chemical confidence, isomer discrimination, and spatial multi-omics integration, undoubtedly remain. In this Perspective, we provide a contemporary overview of the emergent MSI techniques widely used in the plant sciences, with particular emphasis on recent advances in methodological breakthroughs. Having established the detailed context of MSI, we outline both the golden opportunities and key challenges currently facing plant metabolomics, presenting our vision as to how the enormous potential of MSI technologies will contribute to progress in plant science in the coming years.

An ecological-evolutionary perspective on the genomic diversity and habitat preferences of the Acidobacteriota.

Members of the phylum Acidobacteriota inhabit a wide range of ecosystems including soils. We analyzed the global patterns of distribution and habitat preferences of various Acidobacteriota lineages across major ecosystems (soil, engineered, host-associated, marine, non-marine saline and alkaline, and terrestrial non-soil ecosystem) in 248,559 publicly available metagenomic datasets. Classes Terriglobia, Vicinamibacteria, Blastocatellia, and Thermoanaerobaculia were highly ubiquitous and showed clear preference to soil over non-soil habitats, class Polarisedimenticolia showed comparable ubiquity and preference between soil and non-soil habitats, while classes Aminicenantia and Holophagae showed preferences to non-soil habitats. However, while specific preferences were observed, most Acidobacteriota lineages were habitat generalists rather than specialists, with genomic and/or metagenomic fragments recovered from soil and non-soil habitats at various levels of taxonomic resolution. Comparative analysis of 1930 genomes strongly indicates that phylogenetic affiliation plays a more important role than the habitat from which the genome was recovered in shaping the genomic characteristics and metabolic capacities of the Acidobacteriota. The observed lack of strong habitat specialization and habitat transition driven lineage evolution in the Acidobacteriota suggest ready cross colonization between soil and non-soil habitats. We posit that such capacity is key to the successful establishment of Acidobacteriota as a major component in soil microbiomes post ecosystem disturbance events or during pedogenesis.

Kinematic morphology of low-mass galaxies in IllustrisTNG

ABSTRACT The origin of diverse kinematic morphologies observed in low-mass galaxies is unclear. In this study, we investigate the kinematic morphologies of central galaxies with stellar mass $10^{8.5-9.0}{\rm M}_{\odot }$ at $z=0$ in the TNG50-1 cosmological simulation. The majority of the low-mass galaxies in TNG50-1 are dispersion-dominated, consistent with observations. By tracing the evolutionary histories of simulated low-mass galaxies, we find that while most stars form in rotating cold gas discs, the orientation of the star-forming discs relative to the galaxies may evolve with cosmic time. If the cold gas disc remains aligning with the galaxy during its evolution, stars formed at different times share the same rotational direction, leading to a rotation-dominated system. On the contrary, frequent misalignment of cold gas disc would result in a dispersion-dominated system. In addition, we also find that the two-body scattering can have a non-negligible numerical heating effect on the simulated galaxy morphology, especially at central regions of galaxies and for relatively low-mass galaxies. By comparing results of simulations with different resolutions, our results suggest that the simulated morphology of galaxies is roughly reliable when their number of stellar particles exceeds about $10^{4}$, and bulge morphology of galaxies can not be resolved robustly at the resolution level of TNG50-1.

Structure of Aquifex aeolicus lumazine synthase by cryo-electron microscopy to 1.42 Å resolution.

Single-particle cryo-electron microscopy (cryo-EM) has become an essential structural determination technique with recent hardware developments making it possible to reach atomic resolution, at which individual atoms, including hydrogen atoms, can be resolved. In this study, we used the enzyme involved in the penultimate step of riboflavin biosynthesis as a test specimen to benchmark a recently installed microscope and determine if other protein complexes could reach a resolution of 1.5 Å or better, which so far has only been achieved for the iron carrier ferritin. Using state-of-the-art microscope and detector hardware as well as the latest software techniques to overcome microscope and sample limitations, a 1.42 Å map of Aquifex aeolicus lumazine synthase (AaLS) was obtained from a 48 h microscope session. In addition to water molecules and ligands involved in the function of AaLS, we can observe positive density for ∼50% of the hydrogen atoms. A small improvement in the resolution was achieved by Ewald sphere correction which was expected to limit the resolution to ∼1.5 Å for a molecule of this diameter. Our study confirms that other protein complexes can be solved to near-atomic resolution. Future improvements in specimen preparation and protein complex stabilization may allow more flexible macromolecules to reach this level of resolution and should become a priority of study in the field.

Unveiling the role of taxonomic sufficiency for enhanced ecosystem monitoring

The use of Artificial substrates (AS) as sampling devices addresses challenges in macrofaunal quantitative sampling. While effectively capturing biodiversity patterns, the time-intensitive identification process at the species level remains a substantial challenge. The Taxonomic Sufficiency approach (TS), where only taxa above species level are identified, arises as a potential solution to be tested across different environmental monitoring scenarios. In this paper, we analyzed three AS macrobenthic datasets to evaluate the odds of TS in improving the cost-effective ratio in AS monitoring studies and establish the highest resolution level to detect assemblage changes under different environmental factors. Results indicated that the family level emerged as a pragmatic compromise, balancing precision and taxonomic effort. Cost/benefit analysis supported TS efficiency, maintaining correlation stability until the family level. Results also showed that reducing resolution to family does not entail a significant Loss of Information. This study contributes to the discourse on TS applicability, highlighting its practicality in monitoring scenarios, including spatial-temporal studies, and rapid biodiversity assessments. Additionally, it highlights the “second best approach” of family-level practicality depending on the specific monitoring scenario and recognizes the importance of the species-level “best approach” before applying TS in monitoring studies.

NREM sleep brain networks modulate cognitive recovery from sleep deprivation.

Decrease in cognitive performance after sleep deprivation followed by recovery after sleep suggests its key role, and especially non-rapid eye movement (NREM) sleep, in the maintenance of cognition. It remains unknown whether brain network reorganization in NREM sleep stages N2 and N3 can uniquely be mapped onto individual differences in cognitive performance after a recovery nap following sleep deprivation. Using resting state functional magnetic resonance imaging (fMRI), we quantified the integration and segregation of brain networks during NREM sleep stages N2 and N3 while participants took a 1-hour nap following 24-hour sleep deprivation, compared to well-rested wakefulness. Here, we advance a new analytic framework called the hierarchical segregation index (HSI) to quantify network segregation across spatial scales, from whole-brain to the voxel level, by identifying spatio-temporally overlapping large-scale networks and the corresponding voxel-to-region hierarchy. Our results show that network segregation increased in the default mode, dorsal attention and somatomotor networks during NREM sleep compared to wakefulness. Segregation within the visual, limbic, and executive control networks exhibited N2 versus N3 sleep-specific voxel-level patterns. More segregation during N3 was associated with worse recovery of working memory, executive attention, and psychomotor vigilance after the nap. The level of spatial resolution of network segregation varied among brain regions and was associated with the recovery of performance in distinct cognitive tasks. We demonstrated the sensitivity and reliability of voxel-level HSI to provide key insights into within-region variation, suggesting a mechanistic understanding of how NREM sleep replenishes cognition after sleep deprivation.

Evaluation of genetic markers for the metabarcoding of Australian marsupials from predator scats

Context DNA recovered from predator faeces (scats) can be used to determine the presence of fauna and shed light on their life histories and inter-species interactions. DNA metabarcoding, which involves concurrent amplification and sequencing of DNA from multiple taxa, represents an important advance by enabling the simultaneous detection of multiple species from such samples. Although an attractive proposition, metabarcoding requires ‘universally’ applicable genetic markers that can discriminate among a broad range of taxa, while also targeting sequences that are sufficiently short to be amplified from degraded DNA. Aims To identify, evaluate, and test metabarcoding DNA markers suitable for the detection of marsupials and other Australian fauna from terrestrial predator scats found in nature. Methods We apply a bioinformatic approach using publicly available DNA databases and a locally derived and marker-specific reference-DNA database to evaluate the diagnostic ability and likelihood of amplification of candidate metabarcoding markers for marsupials and other taxa that may be consumed by predators. Key results We identify two markers (12SV5 and 16SMam) that are suitable for use and successfully identify marsupial sequences at a high level of resolution. These markers work best in combination because they bring complementary levels of primer specificity and diagnostic ability in detecting multiple prey species as well as the predator. We also show that these samples work well in predator scats sampled from the wild in Tasmania. Conclusions These markers provide a useful tool for surveying mammalian predators and their prey and could also be applied to eDNA analyses from other sample types. Improvements to the reference database and further development of markers targeting different taxonomic groups will improve the resolution and usefulness of this approach. Implications Metabarcoding of predator scats provides a potent approach to non-invasive wildlife survey that offers the opportunity for the detection of multiple species across all vertebrates.

Evaluating host diet effects on microparasites by measuring the stoichiometry of infrapopulations one cell at a time.

Progress in the field of ecological stoichiometry has demonstrated that the outcome of ecological interactions can often be predicted a priori based on the nutrient ratios (e.g., carbon: nitrogen: phosphorus, C:N:P) of interacting organisms. However, the challenges of accurately measuring the nutrient content of active parasites within hosts has limited our ability to rigorously apply ecological stoichiometry to host-parasite systems. Traditional nutrient analyses require high parasite biomasses, often preventing individual-level analyses. This prevents researchers from estimating variation in the nutrient content of individual parasites within a single host infrapopulation, a critical factor that could define how the ecology of the parasite affects the host-parasite interaction. Here, we explain how energy dispersive technology, a technique currently used to measure the elemental content of free-living microbes, can be adapted for parasitic microbial infrapopulations. We demonstrate the power of accurately quantifying the biomass stoichiometry of individual microbial parasites sampled directly from individual hosts. Using this approach, we show that the stoichiometric composition of two microbial parasites capable of infecting the same host are stoichiometrically distinct and respond to host diet quality differently. We also demonstrate that characteristics of the stoichiometric trait distributions of these infrapopulations were important predictors of host fecundity, a proxy for virulence in this system, and better predictors of parasite load than the mean parasite stoichiometry or our parasite and diet treatments alone. EDS provides a rigorous tool for applying ecological stoichiometry to host-parasite systems and enables researchers to explore the nutritional physiology of host-parasite interactions at a scale that is more relevant to the ecology and evolution of the system than traditional nutrient analyses. Here we demonstrate that this level of resolution provides useful insights into the diet-dependent physiology of microbial parasites and their hosts. We anticipate that this improved level of resolution has the potential to elucidate a range of eco-evo interactions in host-parasite systems that were previously unobservable.

Utilization of satellite data for landslide disaster mitigation in extreme event: a case study June 18, 2016, landslide in Banjarnegara Regency, Indonesia

Abstract Understanding the characteristics of landslides produced by rainfall and soil humidity is critical for reducing the occurrence of landslides. Extreme rain, as an external impact, has been suggested to play a role in landslide development. Many people were killed in a landslide that occurred in the Banjarnegara Regency on June 18, 2016, which was unexpected because June is not Indonesia’s rainy season. El Niño and La Niña events were observed in Indonesia in 2015-2016. The initial hypothesis is that such extreme rain conditions caused this landslide. This study aims to apply an alternative approach to detecting landslides by monitoring soil moisture and rainfall with remote sensing data during extreme events. An analysis of precipitation and moisture data has been carried out before the event and is associated with the El Niño and La Niña phenomena. The findings indicate that the natural environment of Banjarnegara Regency is unique. Landslides occur even during the extreme dry season. Rain still drops, and soil moisture is high. The impact of local variables is more significant than regional conditions. They are still at risk of a landslide during the El Niño phase. During that stage, Banjarnegara Regency’s potential landslide area would continue to be observed. Monitoring needs to be carried out rapidly, with a high level of spatial and temporal resolution. It is possible to resolve it using IMERG and SMAP data.

Algorithm 1044: PyGenStability, a Multiscale Community Detection Framework with Generalized Markov Stability

We present PyGenStability, a general-use Python software package that provides a suite of analysis and visualization tools for unsupervised multiscale community detection in graphs. PyGenStability finds optimized partitions of a graph at different levels of resolution by maximizing the generalized Markov Stability quality function with the Louvain or Leiden algorithm. The package includes automatic detection of robust graph partitions and allows the flexibility to choose quality functions for weighted undirected, directed, and signed graphs and to include other user-defined quality functions.

In-gas-jet laser spectroscopy of No254 with JetRIS

Here we report online results with the in-gas-Jet Resonance Ionization Spectroscopy (JetRIS) apparatus. The S01↔P11 transition of No254 was successfully measured with sub-GHz resolution, marking a fivefold improvement over previous measurements. Recent developments in laser spectroscopy have allowed access to more exotic nuclei, but measurements of the heavy actinide region have been limited by line broadening mechanisms, limiting the precision with which nuclear properties can be deduced from the hyperfine spectrum. JetRIS provides a method to measure the heavy actinide region with a high level of sensitivity and higher resolution than previous experiments. The offline and online characterizations of the system are reported, and future perspectives are presented. Published by the American Physical Society 2024